Competing networks. Collaborating on AI. Without either party surrendering their governance authority.
HIEs compete on network effects — more member hospitals means more data means more value. This creates a structural standoff. HIE A and HIE B cover overlapping geographies with different member hospitals, different consent frameworks, and different technical standards. A pharmaceutical company wants a 50,000-patient cohort spanning both networks. Neither HIE will share raw data with the other. The cohort can't be assembled, the research doesn't happen, and both HIEs lose the contract.
The workaround today is an 18-month DUA negotiation that covers one specific use case and doesn't scale. AlignHealthcareAI solves this at the infrastructure level, not the legal level.
A patient who consented to data sharing through HIE A's framework has that consent respected when HIE B's query engine accesses their record — without the patient re-consenting to a new network. The intersection of what both frameworks permit is what gets queried. No human negotiation required at runtime.
Cryptographic identity management means HIE B's infrastructure can verify exactly which of HIE A's authorized agents is querying, operating within agreed policy scope. No party has to trust the other's internal security posture. The identity assertion is cryptographic, not contractual.
Neither HIE sends raw patient records to a shared location. Queries run inside each HIE's environment. Only aggregated, policy-approved results cross the boundary. The research sponsor gets the cohort insights. Neither HIE exposed their member data to a competitor.
Instead of an 18-month DUA negotiation, both HIEs agree on a machine-readable governance policy deployed into AlignHealthcareAI. Updates are version-controlled code commits — not legal amendments. Audit trails prove compliance automatically.
When insights are generated across combined datasets, the governance layer tracks exactly which HIE's data contributed what proportion of the output. Fair revenue sharing for joint research contracts, without either party revealing their underlying data volume.
EHR vendors can't be the neutral governance fabric between competing health systems — they own the on-premises data and have no incentive for portability. Cloud AI providers can't be trusted with PHI governance when they're also selling the compute. A regional HIE can't federate with a competing HIE without a neutral intermediary.
AlignHealthcareAI has no such conflict. We govern the rules. We don't own the data.
If you advise HIEs and health systems on strategy, AlignHealthcareAI gives you the infrastructure to make your governance agreements machine-enforceable and scalable. You design the policy framework. We encode and enforce it in production. Every HIE you bring onto the platform creates a distribution relationship and positions you as the person who made cross-HIE AI collaboration possible in your region.
We'll show you how two HIEs can jointly power AI research without either surrendering their data or their governance authority.
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